Diversity and distribution of chironomids (Diptera

M. Cantonati, R. Gerecke, I. Jüttner and E.J. Cox (Guest Editors)
Springs: neglected key habitats for biodiversity conservation
J. Limnol., 70(Suppl. 1): 106-121, 2011, DOI:10.3274/JL11-70-S1-08
Diversity and distribution of chironomids (Diptera, Chironomidae) in pristine
Alpine and pre-Alpine springs (Northern Italy)
Valeria LENCIONI*, Laura MARZIALI1) and Bruno ROSSARO2)
Department of Invertebrate Zoology and Hydrobiology, Museo Tridentino di Scienze Naturali, Via Calepina 14, 38122 Trento, Italy
1)
Water Research Institute CNR-IRSA, Via del Mulino 19, 20047 Brugherio (MB), Italy
2)
Department of Agri-food and Urban Systems Protection, Università degli Studi di Milano, Via Celoria 2, 20133 Milano, Italy
*e-mail corresponding author: [email protected]
ABSTRACT
The diversity and distribution of chironomids (Diptera, Chironomidae) were studied in relation to environmental factors in 81
springs under pristine conditions in the Italian Prealps and Alps (Trentino and Veneto, NE-Italy, 46°N, 10-11°E). Each spring was
surveyed once, between May and November, in 2005 or in 2007-2008, within 50 m of the spring’s source (eucrenal). A total of 173
macroinvertebrate samples were collected, in which 26,871 chironomids (including larvae, pupae, pupal exuviae and adults) were
counted. Five subfamilies (Tanypodinae, Diamesinae, Prodiamesinae, Orthocladiinae and Chironominae), 54 genera and 104
species/groups of species were identified. As expected, Orthocladiinae accounted for a large part of specimens (82%), followed by
Diamesinae (10%), Chironominae Tanytarsini (6%) and Tanypodinae (2%). Together the Chironominae Chironomini and
Prodiamesinae contributed less than 0.05% of the fauna. Larvae represented 97.5% of specimens, mostly juveniles (62.6%).
Maximum richness and diversity occurred at intermediate altitudes (ca 900-2100 m a.s.l.). Most taxa were found in a small
proportion of sites, and frequencies declined gradually for more widely distributed species. A high number (67%) of rare (= present
in less than 10% of sites) taxa were found. Three to 27 taxa were identified per spring. The rheocrene/rheo-helocrene springs were
richest in taxa (generally >15 taxa), the mineral spring was poorest, with only three taxa. Most taxa were crenophilous, including
lentic, rheobiontic and bryophilous taxa. A Principal Component Analysis (PCA) was performed including 98 taxa. Axes were
interpreted calculating the correlation coefficients between site scores and 24 environmental factors. The species with the highest
scores were Pseudokiefferiella parva, Corynoneura sp. A, Metriocnemus eurynotus gr., Paratrichocladius skirwithensis and Tvetenia
calvescens. Five clusters of sites were identified with K-means analysis on the basis of the first and second PCA axes and a
Discriminant Analysis was used to detect environmental factors discriminating the clusters: altitude, canopy cover, hydrological
regime, pH, and granulometry as percentage of cobbles and stones. The highly individual nature of springs was highlighted; within
the same river basin, between springs and within a single spring. These results suggest that prudent and conservative land
management should assume that all springs sheltering such unique faunal assemblages need protection.
Key words: Orthocladiinae, biodiversity, eucrenal, spring types, south-eastern Alps
1. INTRODUCTION
As in other freshwater habitats, chironomids dominate many freshwater springs, in abundance and species
number (Lindegaard 1995; Gerecke et al. 1998; Stur &
Wiedenbrug 2006).
Nevertheless compared with other insects, chironomids from springs have been less intensively studied. This is mainly due to the difficulty in identifying
larvae – in some genera even pupae and adults (Orendt
2000a), to species level. In fact, lists of midge species
are rather uncommon in ecological studies and knowledge of the autecology, geonemy and phenology of
spring-dwelling species is still fragmentary compared to
other aquatic habitats (Orendt 2000b). The first works
on spring fauna, focusing at least partly on chironomids,
were the investigations by Bornhauser (1912), Nadig
(1942), Zavřel & Pax (1951) and Thienemann (1954).
Lindegaard (1995) gave a comprehensive review of the
chironomid literature on springs listing 99 references,
and discussed the main factors affecting midge distribution in springs. Over the last ten years, several papers
focused on the invertebrate fauna of Alpine and pre-Alpine springs, and of spring-fed brooks (in Italy*):
Crema et al. (1996)*, Bonettini & Cantonati (1998)*,
Klein & Tockner (2000), Orendt (2000a), Rossaro et al.
(2000)*, Füreder et al. (2001), Rossaro & Bettinetti
(2001)*, Stur et al. (2002), Lencioni & Rossaro
(2005)*, Sambugar et al. (2006)*, Stur & Wiedenbrug
(2006), Lencioni (2007)* and Marziali et al. (2010)*.
Up to 200 chironomid species are reported from cold
European springs, and 73 from Italian Alpine springs,
representing about 20% of the species recorded in
Europe and Italy, respectively (Lindegaard 1995; Crema
et al. 2006; Ferrarese 2006; Lencioni 2007). Nevertheless most crenal systems remain unexplored and no
biotic indexes have yet been developed to determine
their ecological status (Cantonati et al. 2006; Marziali et
al. 2010).
Springs and their organisms are good tools for
monitoring changes in groundwater quality due to
human impact. In particular, chironomids are the most
useful indicators of the surface water quality, as well as
the upper layer of groundwater, because the larvae are
Journal of Limnology 70(Suppl. 1), 2011
Preprint copy
2
affected by organic content and heavy metal load in the
sediments (Lafont & Durbec 1990). Within this context,
two projects (CRENODAT and CESSPA) were recently
financed by two Italian public administrations, the
Autonomous Province of Trento and the Adige Basin
Authority, both focused on springs and their fauna as
tools for monitoring changes in groundwater quality due
to human impact (water abstraction for potable or
hydroelectric use, pesticide contamination, etc.). This
work considers only a selected number of springs
investigated within those frameworks, all natural and so
considered pristine sites.
The aims of this work were to: i) analyse chironomid taxa assemblages in natural springs of alpine
and pre-alpine regions; ii) test whether springs can be
separated into distinct groups according to chironomid
fauna; iii) determine the main environmental factors
structuring chironomid taxa assemblages in mountain
springs.
2. METHODS
2.1. Study area
A total number of 81 springs were investigated,
located in the Italian Prealps (21) and Alps (60)
(Autonomous Province of Trento and Veneto Region,
NE-Italy, 46°N, 10-11°E). They lie in 5 siliceous and in
18 carbonate basins, within a wide altitudinal range
(170-2792 m a.s.l.), and belong to 7 hydromorphological types: rheocrene, helocrene, limnocrene, hygropetric, rheo-helocrene, rheo-hygropetric, rheo-limnocrene
(Tab. 1). One spring (PS1255 Fontane negre, Pale di
San Martino) was mineral. Most springs were perennial,
but 7 were intermittent (Cantonati et al. 2007): AD2314
Amola rock glacier, AD2739 Maroccaro rock glacier,
AN430 Pozza 1 Lago Bagatol, CV1421 Tornante
Slavarè, ML0580 Vajo del Croce, ML0950 Varalta,
OC2792 Val di Pejo rock glacier.
2.2. Chironomid collection
Each spring was surveyed once, between May and
November, in 2005 (CRENODAT project) and in 20072008 (CESSPA project). Chironomid larvae and pupae
were collected in the eucrenal zone (= within 50 m of
the spring's source) of each spring. From one to three
replicates were collected per spring by exploring different substratum typologies, depending on the spring
morphology: a) coarse substratum (>0.2 cm, from
gravel to stones); b) fine substratum (<0.2 cm, from
sand to mud); c) submerged bryophytes. A pond net
(100 µm mesh size) was used for 30 seconds in a) and
b); 50 mL of surface sediment were also taken with a
syringe (50 g) (b). 50 g of bryophytes were collected
and washed in the laboratory to extract animals living
within (c). Extra samples of larvae, pupae, pupal
exuviae and adults were taken using tweezers, drift and
sweep nets. Samples were preserved in 75% ethyl alcohol.
V. Lencioni et al.
Chironomids were mounted on slides and identified
to species/groups of species according to Serra-Tosio
(1971), Pinder (1978), Ferrarese & Rossaro (1981),
Rossaro (1982), Ferrarese (1983), Wiederholm (1983,
1986, 1989), Nocentini (1985), Schmid (1993), Janecek
(1998), Stur & Ekrem (2006), Lencioni et al. (2007a)
and Rossaro et al. (2009).
2.3. Environmental variables
During each biological survey, environmental variables were recorded, including those used for the landscape classification. Altitude was measured by GPS
with an instrument error of about 10-15 m. The percent
grain-size composition of the substratum was evaluated
visually as percentage of gravel, cobbles, sand, silt,
stones and rocks. Water samples were collected in acidcleaned graduated bottles for hydro-chemical analysis
(conductivity, alkalinity, hardness, dissolved oxygen, %
oxygen saturation, pH, nutrients, anions, cations, and
metals). Analyses were performed using standard
methods following the American Public Health Association (APHA, AWWA & WEF 2005). Water temperature was measured with a field multiprobe (Hydrolab). In addition, the canopy cover (shading) was visually estimated in five classes: 0%, 25%, 50%, 75%, and
100%. Discharge was measured using a graduated
bucket, repeating the measurement in different areas of
the spring. Average current velocity was measured with
an OTT propeller-flow meter. Turbidity was recorded
using a portable turbidimeter MicroTPI. More details
are given in Cantonati et al. (2007).
2.4. Statistical analyses
Only semi-quantitative samples collected in the
three main substratum typologies were considered in the
statistical analyses (drift and sweep net samples were
not included); the mean abundance of each taxon per
spring was considered. Rare species were included in
the analysis, as recommended by Smith et al. (2001),
resulting in a total of 98 taxa.
Biological and environmental data were log (x+1)
transformed, except for percentage values which were
arcsine (square root) transformed. Shannon Diversity
Index (Shannon & Weaver 1949) was calculated for
each spring with the MVSP® 3.1 computer package.
Pearson correlations between biological and environmental variables were calculated with STATISTICA® 8.0 computer package (StatSoft Inc. 2007).
Values with p <0.05 were considered significant.
Ordination analysis was carried out by means of the
CANOCO® 4.5 computer package (Ter Braak & Šmilauer 2002). A Detrended Correspondence Analysis
(DCA) was first run to detect whether the data had a
unimodal or a linear structure according to the gradient
length of axes. A gradient length between 2.5 and 4.4
suggested a linear model (Principal Component Analysis, PCA) as more appropriate (Ter Braak & Šmilauer
2002), and four axes were calculated.
Chironomidae in mountain springs
3
Tab. 1. General characteristics of the 81 springs sampled within the CRENODAT and CESSPA Projects. Spring code: letters =
Mt. group, numbers = altitude as m a.s.l. R = Rheocrene, HE = Helocrene, HY = Hygropetric, L = Limnocrene, RHE = RheoHelocrene, RHY = Rheo-Hygropetric, RL = Rheo-Limnocrene. Altitude is given as m a.s.l.
Project
Spring code
Spring name
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CESSPA
AD0905
AD1077
AD1235
AD1300
AD1665
AD1790
AD2314
AD2739
LD0584
LD0720
LD0928
LD0930
LD1400
LD1502
AN0430
AN1000
AN1474
AN1578
AN1950
BR0470
BR0658
BR0679
BR0790
BR0950
BR1315
BR1358
BR1379
BR1436
BR1605
BR1765
CS1350
CA1642
CA2153
VZ1178
MC1115
PS1255
PS1880
CV0250
CV0854
CV0962
CV0992
CV1084
CV1200
CV1280
CV1421
CV1433
CV1435
CV1575
CV1623
CV1655
CV1685
CV1855
CV2182
LT1240
MD1670
MD1871
OC2056
OC2792
PG0453
SL1724
AT0972
MB0335
MB0385
Vermongo bassa
Frana edene
Ponte Prese
Borzago
Ponte delle Cambiali
Lago di Nambino
Amola rock glacier
Maroccaro rock glacier
Fontanone
Fiavè
Del Graì
Tof della glera alta
Cortelì
Tormendos
Pozza 1
Vergnana
Fondo
Palu Longià
Bordolona
Maso Gori
Faè 2
Tovare
Sass Ross
Acqua fredda
Valagola
Nambi
Rislà 3
Scala di brenta
Rivularia
Corna Rossa
Monzon
Teleferica Brusà
Bual del passetto
Paul
Poloni
Fontane negre
Salto busa dei Laibi V. Venegia
Resenzuola palu'
Giardini bassa
Pian Gran
Val tamburli
Pirga Roncegno
Perengola
Val Calamento Telve
Tornante Slavarè
Acq. minerale. leggera Vetriolo
Le mandre
Torbiera di Grugola bassa
Valmaggiore
Busa delle rane
Campigol dei solai
Auzertol
Stellune
Daiano
I ciei Monzon
Fedaia
Belvedere
Val di Pejo rock glacier
Trementina alta
Antermont bassa
Masere
Diaol
Gaon
Region
Mt. Group
Alps
Adamello
Alps
Adamello
Alps
Adamello
Alps
Adamello
Alps
Adamello
Alps
Adamello
Alps
Adamello
Alps
Adamello
Alps
Alpi di Ledro
Alps
Alpi di Ledro
Alps
Alpi di Ledro
Alps
Alpi di Ledro
Alps
Alpi di Ledro
Alps
Alpi di Ledro
Alps
Anauni
Alps
Anauni
Alps
Anauni
Alps
Anauni
Alps
Anauni
Alps
Brenta
Alps
Brenta
Alps
Brenta
Alps
Brenta
Alps
Brenta
Alps
Brenta
Alps
Brenta
Alps
Brenta
Alps
Brenta
Alps
Brenta
Alps
Brenta
Alps Catinaccio Sassolungo
Alps
Cima d'Asta
Alps
Cima d'Asta
Alps Cime Bocche Viezzena
Alps
Corno Mezzorona
Alps
Gruppo Pale
Alps
Gruppo Pale
Alps
Lagorai
Alps
Lagorai
Alps
Lagorai
Alps
Lagorai
Alps
Lagorai
Alps
Lagorai
Alps
Lagorai
Alps
Lagorai
Alps
Lagorai
Alps
Lagorai
Alps
Lagorai
Alps
Lagorai
Alps
Lagorai
Alps
Lagorai
Alps
Lagorai
Alps
Lagorai
Alps
Latemar
Alps
Marmolada
Alps
Marmolada
Alps
Ortles-Cevedale
Alps
Ortles-Cevedale
Alps
Paganella Gazza
Alps
Sella
Prealps Altop Folgaria Tonezza
Prealps
Baldo
Prealps
Baldo
Province
Lithology
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Verona
limestone
limestone
siliceous granite
siliceous granite
siliceous granite
siliceous granite
siliceous granite
siliceous granite
limestone
limestone
limestone
limestone
limestone
limestone
siliceous granite
limestone
limestone
siliceous porphyry
siliceous metamorphic
limestone
limestone
limestone
limestone
limestone
limestone
limestone
limestone
limestone
limestone
limestone
limestone
siliceous metamorphic
siliceous metamorphic
limestone
limestone
limestone
limestone
limestone
limestone
siliceous porphyry
limestone
limestone
siliceous porphyry
siliceous metamorphic
siliceous granite
limestone
siliceous porphyry
siliceous granite
siliceous porphyry
siliceous granite
siliceous porphyry
siliceous porphyry
siliceous porphyry
limestone
limestone
limestone
siliceous metamorphic
siliceous granite
limestone
limestone
limestone
limestone
limestone
(continued)
Altitude Type
905
1077
1235
1300
1665
1790
2314
2739
586
720
928
930
1400
1502
430
1000
1474
1578
1950
470
658
679
790
950
1315
1358
1379
1436
1605
1765
1350
1642
2153
1178
1115
1255
1880
250
854
962
992
1084
1200
1280
1421
1433
1435
1575
1623
1655
1685
1855
2182
1240
1670
1871
2056
2792
453
1724
972
335
385
R
R
R
R
R
RHE
R
R
R
RHE
R
R
R
RHY
R
R
RHE
HE
RHE
R
R
R
RHY
R
R
R
R
HY
RHY
R
RHE
RHE
R
RL
R
RHY
R
R
RHE
R
R
R
R
R
R
HY
R
HE
RHE
R
R
R
R
R
R
R
R
R
R
L
R
R
R
4
V. Lencioni et al.
Tab. 1. Continuation.
Project
Spring code
Spring name
Region
Mt. Group
Province
Lithology
CESSPA
CESSPA
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CRENODAT
CESSPA
CESSPA
CESSPA
CRENODAT
CESSPA
CESSPA
CESSPA
CRENODAT
CRENODAT
CRENODAT
MB0445
MB0517
MB1440
BS0705
BS1527
BC0170
BC0503
BC0565
ML0533
ML0580
ML0950
MP0656
MP0676
MP0690
MP0924
MP1566
SC0250
VF0745
Prealba
Lodrone
Tolghe d
Coel
Viotte
Lago Bagatol
Madonina Val Lomasona
Laurel
Biasetti
Vajo del Croce
Varalta
Vallarsa
Biuchele Speccheri
Cocher
Fondo Comperlon
Sette albi
Ramon Freddo Fontanazzo
Madonna del Sass Mezzano
Prealps
Prealps
Prealps
Prealps
Prealps
Prealps
Prealps
Prealps
Prealps
Prealps
Prealps
Prealps
Prealps
Prealps
Prealps
Prealps
Prealps
Prealps
Baldo
Baldo
Baldo
Bondone Stivo
Bondone Stivo
Brento Casale
Brento Casale
Brento Casale
Lessini
Lessini
Lessini
Pasubio
Pasubio
Pasubio
Pasubio
Pasubio
Sette Comuni
Vette Feltrine
Verona
Trento
Trento
Trento
Trento
Trento
Trento
Trento
Verona
Verona
Verona
Trento
Trento
Trento
Trento
Trento
Trento
Trento
limestone
limestone
limestone
limestone
limestone
limestone
limestone
limestone
limestone
limestone
limestone
limestone
limestone
limestone
limestone
limestone
limestone
limestone
Altitude Type
445
517
1440
705
1527
170
503
565
533
580
950
656
676
690
924
1566
250
745
R
R
R
R
R
R
L
R
RHE
L
R
R
R
RHE
R
HY
R
HY
Fig. 1. Water temperature in relation to altitude.
The resulting ordination axis scores were interpreted
against 24 environmental factors (Appendix 1) by
calculating Pearson's product-moment correlation
coefficients.
A K-means Cluster Analysis was carried out to
cluster sites into similar groups based on chironomid
taxon assemblages, considering site scores of the first
two PCA axes as variables. K-means with five groups
gave results of major ecological relevance, compared
with K-means performed with 3, 4, 6 and 7 groups. A
Discriminant Analysis based on the Wilk's lambda test
was performed to detect the environmental factors separating the 5 K-means groups. Values with p <0.05 were
considered significant.
3. RESULTS
3.1. Environmental features in the springs
In table 2 the main physico-chemical and hydromorphological features of the 81 springs are shown. The
study sites are rather heterogeneous, with wide ranges
for all parameters. For example, water temperature
ranged from 0.8 to 14.2 °C, % oxygen saturation from
35 to 105%, pH from 6.3 to 8.3, conductivity from 16 to
2120 µS cm-1, sulphate from 0.82 to 1368 mg L-1,
nitrate nitrogen from 20 to 2853 µg L-1, total phosphorus from 1.8 to 73 µg L-1, orthophosphate from 0.8 to 48
µg L-1 and silica from 0.6 to 13 mg L-1. A strong correlation was found between altitude and water temperature (R2 = 0.63, p <0.01) (Fig. 1), the latter decreasing
with increasing altitude. Generally, the lowest values of
water temperature, pH, conductivity and nutrients were
recorded at the springs located at highest altitudes, in
siliceous basins of the Mt. Groups Adamello, OrtlesCevedale and Lagorai (Appendix 1). More details are
given in Cantonati et al. (2007).
3.2. Chironomid diversity and distribution
A total of 173 replicates of macroinvertebrates were
collected, in which 45% (= 26,871 specimens including
larvae, pupae, pupal exuviae and adults) were chironomids.
Chironomidae in mountain springs
5
Tab. 2. List of chironomid taxa in the 81 springs investigated. Substratum and spring type preferences are reported in bold,
variables significantly (p <0.05) correlated to a specific taxon. R= Rheocrene, HE= Helocrene, HY= Hygropetric, L=
Limnocrene, RHE= Rheo-Helocrene, RHY= Rheo-Hygropetric, RL= Rheo-Limnocrene. *= species new to the Italian
springs; ** = previously reported as Genus spp.; † species new to Italy. Empty cells when no association can be given (too
low abundance or equal distribution of the taxon within microhabitats). ●: crenophilous-crenobiont taxa.
Subfamily
Species
Species code
Substratum preference
Tanypodinae
Nilotanypus dubius (Meigen, 1804)*
Apsectrotanypus sp.*
Psectrotanypus sp.*
Krenopelopia sp.
Macropelopia fittkaui Ferrarese & Ceretti, 1987
Macropelopia nebulosa (Meigen, 1804)*
Macropelopia notata (Meigen, 1818)
Natarsia sp.*
Thienemannimyia sp.*
Trissopelopia sp.
Zavrelimyia sp.
Diamesa aberrata Lundbeck, 1889
Diamesa cinerella Meigen, 1935*
Diamesa dampfi gr.
Diamesa incallida (Walker, 1856)
Diamesa insignipes Kieffer, 1908
Diamesa latitarsis gr.
Diamesa starmachi Kownacki & Kownacka, 1970*
Diamesa steinboecki Goetghebuer, 1933*
Diamesa tonsa (Walker, 1856)*
Diamesa vaillanti Serra-Tosio, 1972*
Potthastia gaedii (Meigen, 1838)*
Pseudodiamesa branickii (Nowicki, 1873)
Pseudokiefferiella parva (Edwards, 1932)
Prodiamesa olivacea (Meigen, 1818)
Acamptocladius reissi Cranston & Sæther, 1981
Brillia bifida (Kieffer, 1909 )
Brillia longifurca Kieffer, 1921*
Bryophaenocladius spp.*
Chaetocladius dentiforceps (Edwards, 1929)**
Chaetocladius perennis (Meigen, 1830)**
Chaetocladius piger gr.**
Chaetocladius vitellinus gr.**
Corynoneura lobata Edwards, 1924**
Corynoneura scutellata Winnertz, 1846**
Corynoneura sp.A**
Cricotopus annulator Goetghebuer, 1927*
Cricotopus fuscus (Kieffer, 1909)
Cricotopus tremulus (Linnaeus, 1756)*
Cricotopus trifascia Edwards, 1929*
Diplocladius cultriger Kieffer, 1908*
Eukiefferiella brehmi gr.*
Eukiefferiella brevicalcar (Kieffer, 1911)
Eukiefferiella claripennis Lundbeck, 1898
Eukiefferiella coerulescens (Kieffer, 1926)*
Eukiefferiella cyanea Thienemann, 1936*
Eukiefferiella devonica gr.
Eukiefferiella gracei gr.
Eukiefferiella minor (Edwards, 1929)
Eukiefferiella similis Goetghebuer, 1939*
Eukiefferiella tirolensis Goetghebuer, 1938*
Heleniella serratosioi Ringe, 1976
Heterotanytarsus apicalis (Kieffer, 1921)
Heterotrissocladius marcidus (Walker, 1956)
Hydrobaenus sp.*
Krenosmittia borealpina (Goetghebuer, 1944)**
Limnophyes spp.
Limnophyes asquamatus Søgaard Andersen, 1937*
Metriocnemus fuscipes gr.
Metriocnemus eurynotus gr.
N_dubius
Apsectrot
Psectrot
Krenopel
M_fittkaui
M_nebulosa
M_notata
Natarsia
Thienema
Trissope
Zavrelim
D_aberra
D_cinere
D_dampfi
D_incall
D_insign
D_latita
D_starma
D_steinb
D_tonsa
D_vailla
P_gaedii
P_branic
P_ parva
P_olivac
A_reissi
B_bifida
B_longif
Bryophae
C_dentif
C_perenn
C_piger
C_vitell
C_lobata
C_scutel
Cory_sp.A
C_annula
C_fuscus
C_tremul
C_trifas
D_cultrig
E_brehmi
E_brevic
E_clarip
E_coerul
E_cyanea
E_devonic
E_gracei
E_minor
E_simili
E_tirole
H_serrat
H_apical
H_marcid
Hydrobae
K_boreal
Limnophy
L_asquam
M_fuscip
M_euryno
sand
silt-mud
sand
●
●
●
Diamesinae
●
●
●
●
●
●
●
●
●
Prodiamesinae
Orthocladiinae
●
●
●
●
●
●
●
●
●
●
●
●
Spring type
preference
HE
HY
silt-mud
silt-mud
cobbles/stones
bryophytes
bryophytes
sand
silt-mud, sand
cobbles/stones
bryophytes
bryophytes
cobbles/stones
cobbles/stones
cobbles/stones
bryophytes
cobbles/stones
cobbles/stones
cobbles/stones
cobbles/stones
bryophytes
cobbles/stones
silt-mud
bryophytes
gravel/cobbles
bryophytes
bryophytes
cobbles/stones
silt-mud
cobbles/stones
silt-mud
gravel, bryophytes
bryophytes
bryophytes
cobbles/stones
cobbles/stones
bryophytes
silt-mud
bryophytes, cobbles/stones
silt-mud
cobbles/stones
cobbles/stones
cobbles/stones
sand
stones/rock, bryophytes
bryophytes
bryophytes
sand, silt
silt-mud
silt-mud
bryophytes
cobbles/stones
bryophytes
bryophytes
bryophytes
(continued)
L, HE
RHY
L
RHY
HE
R
RHE
R
R
R
R
R
R
RHE
RL, HE
RHE
HY
RHE
R
R, RL, HE
R
RHE
R
HY
HY
HY
R
RHY, HY
RHE
HE, RL
R
L
HY
6
V. Lencioni et al.
Tab. 2. Continuation.
Subfamily
Species
●
●
●
●
●
●
●
●
●
●
●
Chironominae
●
●
●
●
Species code
Metriocnemus inopinatus Strenzke, 1950*
M_inopina
Metriocnemus terrester Pagast, 1941*
M_terres
Orthocladius spp.
Orthocl
Orthocladius (Euorthocladius) frigidus (Zetterstedt, 1838)E_frigidu
Orthocladius (Eudactylocladius) fuscimanus Kieffer, 1908*E_fuscim
Orthocladius (Euorthocladius) rivicola Kieffer, 1921
E_rivico
Orthocladius (Symposiocladius) sp.*
Symposio
Parachaetocladius sp.*
Parachae
Paracricotopus niger (Kieffer, 1913)*
Paracric
Parakiefferiella gracillima (Kieffer, 1924)
P_gracil
Parametriocnemus boreolapinus Gouin, 1942
P_boreoa
Parametriocnemus sp.A*
Param_spA
Parametriocnemus stylatus (Kieffer, 1924)
P_stylatus
Paraphaenocladius impensus (Walker, 1856)*
P_impens
Paratrichocladius rufiventris (Meigen, 1830)
P_rufive
Paratrichocladius skirwithensis (Edwards, 1929)
P_skirwi
Paratrissocladius excerptus (Walker, 1856)*
P_excerp
Parorthocladius nudipennis (Kieffer, 1908)
P_nudipe
Pseudorthocladius sp.*
Pseudort
Pseudosmittia sp.*
Pseudosm
Rheocricotopus chalybeatus (Edwards, 1929)*
R_chalyb
Rheocricotopus effusus (Walker, 1856)
R_effusu
Rheocricotopus fuscipes Kieffer, 1909*
R_fuscip
Stilocladius montanus Rossaro, 1979*
S_montan
Synorthocladius semivirens Kieffer, 1909*
S_semivi
Thienemannia gracilis Kieffer, 1909**
T_gracili
Thienemanniella clavicornis (Kieffer, 1911)**
T_ clavic
Thienemanniella vittata (Edwards, 1924)**
T_vittat
Tvetenia bavarica (Goetghebuer, 1934)
T_bavari
Tvetenia calvescens (Edwards, 1929)
T_calves
Tvetenia verralli (Edwards, 1929)*
T_discol
Paracladopelma sp.*
Paraclad
Krenopsectra fallax Reiss, 1969*
Krenopse
M_arista
Micropsectra aristata Pinder, 1976*
Micropsectra atrofasciata (Kieffer, 1911)*
M_atrofa
Micropsectra bavarica Stur & Ekrem, 2006*
M_bavari
Micropsectra schrankelae Stur & Ekrem, 2006*
M_schran
Micropsectra seguyi Casas & Laville, 1990*
M_seguyi
Micropsectra sofiae Stur & Ekrem, 2006*
M_sofiae
Micropsectra longicrista Stur & Ekrem, 2006** †
M_longic
Rheotanytarsus sp.
Rheotany
Stempellinella sp.
Stempell
Tanytarsus heusdensis Goetghebuer, 1923**
T_heusde
Tanytarsus pallidicornis (Walker, 1856)**
T_pallid
Five subfamilies (Tanypodinae, Diamesinae, Prodiamesinae, Orthocladiinae and Chironominae), 54 genera
and 104 species/groups of species were identified (Tab.
2). Orthocladiinae accounted for 82% of the total chironomid fauna, followed by Diamesinae (10%), Chironominae Tanytarsini (6%) and Tanypodinae (2%).
Together Chironominae Chironomini and Prodiamesinae contributed less than 0.05% of specimens. Larvae
represented 97.5% of the animals, most of which were
juveniles (62.6%).
No significant correlation was found between taxon
richness and Shannon Diversity Index with altitude, the
highest values for both being associated with an
intermediate altitudinal range (Figs 2, 3). Most taxa
occurred at a small proportion of the sites, and frequencies
declined gradually for more widely distributed species. A
high number (68 = 67%) of rare (= present in less than
Substratum preference
Spring type
preference
bryophytes
silt-mud, bryophytes
bryophytes, cobbles/stones
cobbles/stones, bryophytes
cobbles/stones
stones/rock
cobbles/stones
bryophytes, silt-mud
bryophytes
bryophytes
silt-mud
R
silt-mud
silt-mud
cobbles/stones
bryophytes, cobbles/stones
silt-mud
cobbles/stones
cobbles/stones
bryophytes
cobbles/stones
silt-mud
bryophytes, cobbles/stones
bryophytes, cobbles/stones
cobbles/stones
bryophytes, silt-mud
bryophytes, cobbles/stones
cobbles/stones
bryophytes
cobbles/stones, bryophytes
bryophytes
bryophytes, silt-mud
silt-mud
silt-mud, bryophytes
bryophytes, cobbles/stones
silt-mud
cobbles/stones
silt-mud
silt-mud
bryophytes, cobbles/stones
silt-mud
sand
cobbles/stones
silt-mud
R
RHY, HY
R
RHE
RHE
R
R
RL, RHE
R
R
R
RL, HY
RL
L
RL
RHY
R, HY, RHY
RHE
RHE
HE
HY
HY
RL
10% of sites) taxa were found (Fig. 4). Of these, 35
(30%) occurred in only one site. These included several
species of the genera Diamesa and Eukiefferiella, such
as Diamesa cinerella and Diamesa tonsa (both only in
AD1665 Ponte delle Cambiali), Diamesa incallida and
Eukiefferiella tirolensis (in BR1358 Nambi), Diamesa
insignipes (in OC2056 Belvedere), Diamesa latitarsis
gr. (only in AD905 Vermongo Bassa), Diamesa starmachi (in MD1871 Fedaia), Eukiefferiella cyanea (in
BR1436 Scala di Brenta), Eukiefferiella devonica gr. (in
MP0676 Biuchele Speccheri), Eukiefferiella similis (in
ML0533 Biasetti). Other very rare taxa were
Paraphaenocladius impensus (in CV0250 Resenzuola
Palù), Paratrissocladius excerptus (in AD905 Vermongo Bassa), Rheocricotopus chalybeatus (in MB0385
Gaon), Rheotanytarsus sp. (in AD1665 Ponte delle
Cambiali) and Paracladopelma sp. (in AN1474 Fondo).
Chironomidae in mountain springs
7
Fig. 2. Number of taxa per spring in relation to altitude (m a.s.l.).
Fig. 3. Median, 25th, 75th percentile of Shannon Diversity Index in relation to altitude (m a.s.l.). Height of box (H)= 25th-75th
percentile; whiskers = non-outlier values comprised within an interval of 1.5 x H.
Fig. 4. Number of taxa in relation to number of sites occupied.
8
V. Lencioni et al.
Fig. 5. Abundance-occupancy relationships.
Three taxa were present in at least 50% of the sites
(= common taxa): Tvetenia calvescens, Corynoneura sp.
A and Metriocnemus eurynotus (= hygropetricus) gr.
(Fig. 5). No taxon was present in all 81 sites. Widespread species generally tended to have a relatively
higher abundance than those with restricted distributions. The local abundance of taxa increased (but not
significantly, y = 0.396x - 0.541, R2 = 0.48) with the
number of sites from which they were collected. The
most frequent (= present in at least 50% of sites) and
abundant (= mean density ≥29 ind./spring) taxa were
Tvetenia calvescens and Corynoneura sp. A. Among the
less common taxa, high abundance was observed for
Orthocladius spp. (21% of the sites) and Paratrichocladius skirwithensis (36% of the sites) (Fig. 5). More than
fifty taxa were new to Italian springs (Tab. 2) and one,
Micropsectra longicrista, was new to Italy, found in the
rheocrene Valagola (BR1315). In contrast, some previously recorded species (Ferrarese 2006) were not found,
such as the ubiquist Chironominae Chironomus lacunarius (Wülker 1973), and the crenophilous Podonominae Paraboreochlus minutissimus (Strobl 1894).
From 3 to 27 taxa were identified per spring. Only
five springs hosted more than 20 taxa and more than
130 individuals. Three of these, all rheocrenes and at
altitudes >1470 m a.s.l., are located in the Lagorai Mt.
Group, in siliceous basins (porphyry) (CV1685 Campigol dei Solai, CV2182 Stellune, CV1855 Auzertol).
The other two, rheo-helocrenes, are both located in the
Anauni Mt. Group, one in a siliceous metamorphic
basin (AN1950 Bordolona) and one on limestone
(AN1474 Fondo). Three to 5 taxa were counted in 8
springs, distributed over seven different Mt. Groups, of
different hydro-morphological types and located mainly
at <1000 m a.s.l. (PS1255 Fontane Negre, rheohygropetric; PG0453 Trementina alta, rheocrene;
ML0580 Vajo del Croce, limnocrene; MP0924 Fondo
Comperlon, rheocrene; CV0992 Val Tamburli,
rheocrene; BC0503 Madonnina Val Lomasona, limnocrene; MB0517 Lodrone, rheocrene; CV1433 Acqua
minerale Vetriolo, hygropetric). The last was the only
mineral (sulphurous) spring (SO42- = 409 mg L-1, conductivity = 1239 µS cm-1), in which the lowest richness
was recorded (Limnophyes asquamatus, Bryophaenocladius spp. and Paratrichocladius skirwithensis).
Diversity was higher in mixed-type springs, such as
rheo-helocrenes, rheo-hygropetric and rheo-limnocrenes, but lowest in the limnocrenes. The widest range of
diversity values was recorded in the rheocrenes (Fig. 6).
44% of specimens were found on the coarse substratum (>0.2 cm), 38% in submerged bryophytes and
18% in the finer sediment. Diversity was highest in
coarse substratum (1.89), followed by fine substrate
(1.82) and bryophytes (1.78). Thirty-eight taxa were
common to all three substrate types. Sixteen taxa were
exclusive to coarse substrata (Chaetocladius perennis,
Corynoneura lobata, Cricotopus tremulus, Cricotopus
trifascia, Diamesa incallida, Diamesa insignipes, Diamesa latitarsis gr., Diamesa tonsa, Diamesa vaillanti,
Eukiefferiella coerulescens, Eukiefferiella cyanea,
Macropelopia notata, Potthastia gaedii, Rheocricotopus
chalybeatus, Orthocladius (Symposiocladius) sp. and
Tanytarsus heusdensis). Thirteen taxa were exclusive to
fine substrata: Corynoneura scutellata, Eukiefferiella
brehmi gr., Eukiefferiella claripennis gr., Heterotanytarsus apicalis, Macropelopia fittkaui, Micropsectra
bavarica, Parachaetocladius sp., Paraphaenocladius
impensus, Paratrissocladius excerptus, Prodiamesa
olivacea, Paracladopelma sp., Tanytarsus pallidicornis.
Nine taxa were found only in bryophytes (Chaetocladius dentiforceps, Diplocladius cultriger, Eukiefferiella
similis, Limnophyes asquamatus, Metriocnemus inopinatus, Natarsia sp., Parakiefferiella gracillima,
Paracricotopus niger, Pseudosmittia sp.).
No taxa were exclusive to helocrenes, limnocrenes
and rheo-limnocrenes. Three taxa were captured only in
Chironomidae in mountain springs
9
Fig. 6. Median, 25th, 75th percentile of Shannon Diversity Index in relation to spring types. Height of box (H)= 25th-75th percentile;
whiskers = non-outlier values comprised within an interval of 1.5 x H. R= Rheocrene, RHE= Rheo-Helocrene, HE= Helocrene, L=
Limnocrene, RHY= Rheo-Hygropetric, HY= Hygropetric, RL= Rheo-Limnocrene.
hygropetric springs (Micropsectra bavarica, Eukiefferiella cyanea, Limnophyes asquamatus), nineteen in
rheocrenes (Corynoneura scutellata, Cricotopus trifascia, Diamesa aberrata, D. incallida, D. insignipes, D.
latitarsis gr., D. steinboecki, D. vaillanti, Eukiefferiella
brehmi gr., E. devonica gr., Hydrobaenus sp.,
Metriocnemus inopinatus, Potthastia gaedii, Parakiefferiella gracillima, Paraphaenocladius impensus, Pseudorthocladius sp., Pseudosmittia sp., Rheocricotopus
chalybeatus, Symposiocladius sp.), three in rheohelocrenes (Eukiefferiella similis, Paracricotopus niger,
Paracladopelma sp.), and one in the rheo-hygropetric
type (Macropelopia notata).
Cold-stenothermal taxa (such as all Diamesa species) were restricted to stations located in siliceous
basins at the highest altitudes (>1400 m a.s.l.), where
the lowest temperatures, pH, conductivity and canopy
cover (<50%) were recorded.
3.3. Chironomid community in relation to
environmental factors
Results of PCA, K-means Cluster Analysis and of
Discriminant Analysis are given in tables 3, 4 and in
figures 7, 8, 9. Four eigenvalues were selected by the
Principal Component Analysis: 0.157, 0.085, 0.072 and
0.06 accounting for 37.4% of the total variance.
Five clusters were identified on the basis of the chironomid taxon assemblages in the 81 springs (K-mean
analysis) (Tab. 3, Fig. 7). The Discriminant Analysis
selected 6 environmental variables as best associated
with the observed chironomid assemblages (Tab. 4).
A water temperature - altitude gradient was found
along the first PCA axis (Fig. 8). Water temperature was
positively correlated to conductivity, pH, high level of
nutrients, canopy cover and limestone substratum,
whereas altitude was correlated with current velocity,
discharge, oxygen content, presence of bryophytes,
coarse substratum. A canopy cover-lithology gradient
was found along the second axis. Species-environment
relationships accounted for 48.6% of total variance.
Rheocrene and hygropetric springs grouped in the first
(cluster D, E) and fourth (clusters A, E) quadrants, whereas
most of helocrenes and rheo-helocrenes grouped in the
second (cluster B) and third (cluster C) quadrants (Fig. 7).
Limnocrene springs occurred in different clusters (one in
cluster B, two in cluster C, and one rheo-limnocrene in
cluster E). Sites richest in nutrient and organic debris were
grouped in cluster B, with higher canopy cover that ensures
shading and more allochtonous food. All the intermittent
springs grouped in cluster C, and cold, high-altitude
springs with less nutrients in cluster A. The taxa best
associated with the site clusters were Paratrichocladius
skirwithensis and Pseudokiefferiella parva (cluster A),
Metriocnemus eurynotus (cluster D), Tvetenia calvescens
and Corynoneura sp. A (cluster E) (Fig. 9).
4. DISCUSSION
The percentage distribution of taxa within chironomid subfamilies was in accordance with previous
studies (Lindegaard 1995; Stur et al. 2005; Stur &
Wiedenbrug 2006), with Orthocladiinae as the most
frequent, taxon-richest and abundant subfamily. Many
cold stenothermal and rheophilous taxa were found,
based on the prevalence of cold and rheocrene springs.
Most larvae were juveniles, highlighting the role of stable crenal habitats, as nurseries, even for non-crenophilous species, and as a refuge against water current and
abrupt environmental changes.
10
V. Lencioni et al.
Tab. 3. K-means clusters of sites according to chironomid community.
AD1665
AN1950
BR1765
CA2153
CV2182
MD1871
OC2056
PS1880
AD1790
AN1000
AN1578
AT0972
BC0565
BR0470
BR0790
BR0950
BS0705
BS1527
CS1350
CV0250
CV0854
CV0962
CV1084
LD0584
LD0720
LD0930
LD1400
LT1240
MB0335
MB1440
MC1115
MP0656
PG0453
SC0250
SL1724
VF0745
AD1077
AD2314
AD2739
AN0430
BC0170
PC
Aaxis 1
PC
Aaxis 2
K-means
Cluster
Distance
-0.0768
0.9147
0.4515
0.4943
0.5422
0.5851
0.2026
0.0322
-0.293
-0.3259
-0.1638
-0.2594
0.0281
-0.224
-0.1976
-0.1464
-0.1987
-0.1897
0.0272
-0.0112
-0.2703
-0.1998
0.093
0.0377
-0.3717
-0.2155
-0.1672
-0.1353
-0.2753
-0.348
-0.2976
-0.2433
-0.1798
-0.1561
-0.0725
-0.3853
-0.1792
-0.2365
-0.4391
-0.3885
-0.3314
-0.6126
-0.5382
-0.5615
-0.7107
-0.7681
-0.5342
-0.3456
-0.5791
0.0321
0.0569
0.1931
0.2323
0.1927
0.0314
0.0943
0.4368
0.2395
0.0191
0.2032
0.1577
0.2479
0.4259
0.2619
0.2265
0.0826
0.2118
0.0811
0.4194
0.1508
0.1111
0.0383
0.2847
0.0403
0.0032
-0.0603
0.1361
-0.1235
-0.592
-0.2722
-0.0491
-0.1147
A
A
A
A
A
A
A
A
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
C
C
C
C
C
0.33
0.37
0.04
0.12
0.17
0.14
0.21
0.26
0.12
0.13
0.03
0.07
0.15
0.10
0.05
0.20
0.06
0.10
0.15
0.12
0.09
0.19
0.21
0.16
0.14
0.04
0.06
0.18
0.07
0.12
0.12
0.10
0.09
0.11
0.18
0.14
0.12
0.33
0.11
0.07
0.02
BC0503
BR0679
CA1642
CV0992
CV1433
CV1575
MB0385
MB0445
MB0517
MD1670
ML0533
ML0580
ML0950
MP0676
MP0690
MP0924
OC2792
PS1255
AD1235
AN1474
BR0658
BR1605
CV1280
CV1623
CV1855
LD1502
MP1566
AD0905
AD1300
BR1315
BR1358
BR1379
BR1436
CV1200
CV1421
CV1435
CV1655
CV1685
LD0928
VZ1178
PC
Aaxis 1
PC
Aaxis 2
K-means
Cluster
Distance
-0.4723
-0.2583
-0.3433
-0.3437
-0.445
-0.086
-0.2961
-0.4692
-0.5076
-0.3156
-0.4608
-0.4812
-0.4565
-0.4097
-0.3527
-0.4551
-0.0599
-0.3197
0.7271
0.1475
0.5351
0.6548
0.227
0.2383
0.2769
0.5142
0.3253
0.3258
0.285
0.9106
0.2759
0.5455
0.238
0.5238
0.536
0.5177
0.6644
1.2396
0.1845
0.2105
-0.0498
-0.1505
-0.1889
-0.0568
-0.2752
-0.2014
-0.1073
-0.0699
-0.0455
-0.0656
-0.0305
-0.0699
-0.0804
-0.102
-0.0205
-0.1187
-0.3018
-0.1605
0.868
0.5622
0.3398
0.3387
0.3419
0.2728
0.2692
0.2618
0.5209
-0.014
0.0712
0.2003
-0.2281
-0.1691
0.0134
0.1428
-0.0281
-0.0904
-0.0601
0.0051
-0.1644
-0.1078
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
D
D
D
D
D
D
D
D
D
E
E
E
E
E
E
E
E
E
E
E
E
E
0.11
0.07
0.03
0.06
0.12
0.19
0.05
0.10
0.13
0.06
0.11
0.10
0.09
0.05
0.09
0.07
0.24
0.03
0.39
0.21
0.11
0.19
0.14
0.16
0.14
0.14
0.09
0.12
0.17
0.34
0.21
0.10
0.19
0.13
0.03
0.04
0.12
0.53
0.24
0.21
Tab. 4. Discriminant Analysis results. Wilks' Lambda: 0.066 approx. F (96,21)=2.18,
p <0.001.
Environ. variable
Wilks'
Partial
F-remove
p-level
Toler.
1-Toler.
Altitude
pH
% cobbles
% stones
Canopy cover
Regime
0.086
0.087
0082
0.087
0.086
0.081
0.772
0.756
0.806
0.763
0.771
0.811
3.907
4.284
3.195
4.112
3.939
3.081
0.007
0.004
0.020
0.006
0.007
0.024
0.229
0.173
0.334
0.385
0.444
0.363
0.771
0.827
0.666
0.615
0.556
0.637
Chironomidae in mountain springs
11
Fig. 7. Plot of springs in the plane of the first two PCA axes. Different colours and icons indicate different K-means clusters (A-E) of
sites.
Fig. 8. Plot of environmental variables best correlated to site scores (axes 1 and 2) of PCA based on the chironomid communities
living in the 81 sampled springs. In bold, the six variables selected by the Discriminant Analysis separating the 5 K-means clusters of
sites.
This was also observed for the hyporheic zone of
alpine streams, which are known to play a similar role
for chironomids and other freshwater invertebrates
(Lencioni et al. 2006).
Taxon richness and diversity had their maxima at
intermediate altitudes (between about 900 and 2100 m
a.s.l.), as noted by other authors (Orendt 2000a). As
expected, the rheo-helocrene springs were the most species rich, being a mosaic of different niches (Lindegaard
1995; Cantonati et al. 2006; Sambugar et al. 2006).
Many captured taxa were crenophilous, as defined by
Thienemann (1954), Lindegaard (1995), Stur et al.
(2005), Stur & Wiedenbrug (2006) and Novikmec et al.
(2007) (Tab. 2). Lindegaard (1995) only defined one of
these species, Macropelopia fittkaui, as a true crenobiont. However, according to Stur & Wiedenbrug (2006),
due to the difficulty of recognising true crenobiont species within the chironomids, it is preferable to consider
crenophilous taxa and crenobionts together, as a single
category.
On the basis of our results, some species might be
defined as lentic, rheobiontic (including madicoloushygropetric) and bryophilous, based on their occurrence
in specific habitats/spring types (see Tab. 2). Our findings generally confirmed what was already known for
such taxa, albeit with some exceptions. For example,
Macropelopia notata was found associated with the
rheo-hygropetric spring type, but was previously
reported as typical of moss-rich helocrenes (Stur et al.
2005); Limnophyes asquamatus and Corynoneura
scutellata occurred as madicolous and rheobionts
respectively, not as ubiquists (Lindegaard 1995); Ortho-
12
V. Lencioni et al.
Fig. 9. Plot of species in the first two PCA axes. Only the names of the taxa accounting for the largest quote of variance are reported.
cladius (Eudactylocladius) fuscipes was not associated
with bryophytes as previously reported (Lindegaard
1995; Stur & Wiedenbrug 2006); Paraphaenocladius
impensus occurred as a rheobiont, but has been known
as terrestrial/madicolous (Lindegaard 1995; Stur &
Wiedenbrug 2006).
More than 50% of species are new for Italian springs
and one is new to Italy, highlighting the current poor
knowledge of the fauna in Italian springs (Lencioni
2007).
With respect to their the trophic role, Orthocladiinae
(grazing organisms) were particularly common in
bryophytes, Diamesinae were associated with coarse
substrata, expected from their rheophilous habit. The
predators or omnivores (Tanypodinae) were present in
all microhabitat types, while the collectors (Tanytarsini,
Prodiamesinae and Chironomini) were abundant in
sediments.
The relationships observed between the distribution
and abundance of common and rare species suggests
that the chironomid fauna cannot be considered nested,
even if some level of nestedness was highlighted and a
few hotspots of chironomid biodiversity were found
(e.g., the rheocrene spring CV1685 Campigol dei Solai
accounted for 27 taxa, including 100% of the most
common species and 13% of the rarest). Most taxa were
found at a small proportion of the sites and frequency
categories declined gradually for more widely distributed species. This distribution pattern has also been
observed for blackflies and other aquatic insects from
montane freshwater systems (Malmqvist et al. 1999;
Lencioni et al. 2007b).
Species were distributed according to altitude, substratum composition, pH and canopy cover (and to those
factors significantly correlated with them). These four
factors were previously reported as determining the
composition of macroinvertebrate assemblages (e.g.,
Glazier 1991; Smith et al. 2001; von Fumetti et al.
2006). However, as only 37.4% of the total variance
was explained by the four principal canonical axes,
other environmental factors may be important, such as
competition and predation (Hahn 2000). No clear association with basin geology was highlighted, apart from
the indirect link via positive correlations with pH and
conductivity.
As observed by other authors (e.g., Smith et al.
2001), a transition from one spring type to another
appears to be gradual, and there is almost a continuum
between "traditional" types (most types were distributed
in all K-means clusters).
Finally, as expected (Smith & Wood 2002; Smith et
al. 2003; von Fumetti et al. 2006), intermittent springs,
Chironomidae in mountain springs
including three rock glaciers (AD2314 Amola, AD2739
Maroccaro, OC2792 Val di Pejo), hosted fewer taxa
than the permanent ones, and none of the taxa was
exclusive to such springs.
In conclusion, the highly individual nature of the
springs was evident; within the same river basin, within
a spring and between different springs. This suggests
that prudent and conservative land management should
assume that all springs need protection to conserve their
faunal assemblages. Deeper knowledge of species
autecology is needed to assess and monitor the
ecological status of springs. Therefore, studying the
distribution and dynamics of the characteristic spring
fauna will help to identify the most appropriate measures to mitigate adverse man-made effects on springs, to
which, due to their small spatial extent, they are
extremely vulnerable.
ACKNOWLEDGEMENTS
The authors thank all colleagues who participated in
chironomid collection, including Daniele Fattori,
Nicoletta Verdari, Nicola Angeli, Daniel Spitale, Massimiliano Tardio, Ermanno Bertuzzi. The research was
carried out within two projects: 1) the CRENODAT
Project ("Biodiversity assessment and integrity evaluation of springs of Trentino - Italian Alps - and long-term
ecological research") financed by the Autonomous
Province of Trento (Italy) (2004-2007) and coordinated
by Marco Cantonati (Museo Tridentino di Scienze
Naturali, Trento, Italy); 2) the CESSPA Project "Censimento e Studio delle Sorgenti e dei Pozzi del territorio
alpino e prealpino di competenza dell'Autorità di Bacino
del Fiume Adige" financed by the Authority of the
Adige River (2007-2009) and coordinated by Leonardo
Latella (Museo Civico di Storia Naturale, Verona,
Italy). Part of data were included in the Master thesis by
Gianni Sartori (University of Padua, Italy, 2008/2009).
Finally, the authors thank two anonymous reviewers for
their useful comments and suggestions and Eileen J.
Cox for English revision.
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Chironomidae in mountain springs
15
A P P E N D I X
0.29
0.52
0.04
0.06
0.07
0.40
0.15
0.44
0.24
2.95
0.17
0.09
0.28
0.98
0.50
0.56
0.53
0.46
0.23
0.64
1.47
0.07
0.12
0.36
0.11
0.12
0.63
0.20
0.62
0.22
0.60
0.48
0.11
0.03
0.16
0.14
0.02
0.04
6.90
0.49
0.32
0.99
0.40
0.34
0.06
25.6
0.06
0.25
8.6
6.5
6.3
5.9
5.7
4.8
1.0
0.8
8.7
10.1
7.8
7.0
6.8
6.5
11.7
7.1
7.1
7.2
3.9
7.1
14.2
8.7
7.1
7.0
5.4
5.7
4.2
5.7
7.0
4.4
7.8
6.3
5.5
5.7
10.0
7.3
3.4
11.5
9.1
11.7
8.0
9.2
7.2
5.7
6.2
9.1
4.8
5.1
72
90
94
95
97
96
95
105
88
85
81
79
76
78
65
90
83
70
89
100
81
95
92
90
88
89
91
94
93
93
77
79
79
72
65
35
86
63
74
65
86
88
91
78
85
89
93
81
8 232 8 737 2 5.4 <dl
8 393 15 741 1 3.7 <dl
8 198 4 973 10 6.4 <dl
7 35 2 1224 3 6.1 6
7 29 1 354 1 4.6 <dl
7 28 2 297 3 8.0 <dl
6 19 1 1137 1 3.6 <dl
7 26 1 549 3 2.1 <dl
8 313 6 1690 1 2.1 <dl
8 392 10 768 3 7.1 <dl
8 354 3 815 2 1.9 <dl
8 229 2 597 2 4.1 <dl
8 271 7 1467 2 3.5 <dl
8 216 1 1117 2 1.9 <dl
8 473 20 1890 48 6.3 <dl
8 271 7 772 1 5.9 <dl
8 345 5 562 1 2.3 <dl
7 49 3 55 2 5.1 <dl
6 24 4 327 2 4.3 <dl
8 269 1 427 3 0.9 <dl
8 362 2 159 2 6.2 3
8 267 2 272 6 2.8 <dl
8 368 3 318 6 3.3 <dl
8 262 17 884 3 7.2 <dl
8 225 3 738 1 1.9 <dl
8 239 17 625 2 2.8 <dl
8 212 3 746 1 1.2 <dl
8 179 5 716 1 1.3 9
8 241 2 238 1 1.1 <dl
8 221 1 229 3 1.6 <dl
8 301 7 893 13 3.1 <dl
6 19 3 343 1 3.8 <dl
7 16 1 324 1 3.7 <dl
8 230 29 365 1 6.6 <dl
8 120 4 92 6 5.5 <dl
8 2120 1368 112 1 5.8 <dl
8 207 6 247 5 2.6 <dl
8 319 24 902 5 5.8 <dl
8 477 27 2853 2 6.3 <dl
7 44 3 108 2 12.5 <dl
8 299 4 1175 13 3.9 <dl
8 166 37 621 3 7.6 <dl
7 64 2 361 7 10.7 <dl
8 157 25 504 1 6.6 <dl
7 29 4 250 1 3.1 <dl
6 1239 409 20 11 10.7 14210
7 35 2 717 6 5.1 <dl
7 28 3 293 2 5.7 <dl
(continued)
Fe (µg L-1)
15 0 15 7.0
20 0 30 3.0
20 0 20 0.9
20 0 50 12.0
35 5 80 95.0
0
0 10 0.7
30 0 30 0.5
80 0 21 3.5
15 0 30 4.5
0
0
5 0.1
0
0
7 0.1
5 50 40 0.5
15 0
5 0.1
30 50 10 0.04
20 0
5 0.1
20 25 40 0.6
0
0 10 0.5
0
0 10 0.2
25 0 20 4.0
25 40 100 30.0
0
0 13 0.5
20 5 30 7.0
0 30 20 1.0
20 0 15 1.5
15 0 15 1.0
25 0 28 20.0
10 0 30 1.5
15 45 20 0.5
10 30 5 0.3
15 0 40 4.5
35 0 30 1.0
0
0
1 1.5
30 35 35 0.7
30 5 15 2.0
45 0 10 0.3
0
0
6 0.3
15 5 35 7.0
0
0 20 3.0
5 50 5 0.01
50 0 40 0.5
15 10 25 1.0
5
0
5 0.1
10 25 35 3.0
0
0 15 4.0
25 5 30 1.0
0 100 5 3.5
0
0 25 5.0
0
0
1 1.0
SiO2 (mg L-1)
15
10
10
10
5
30
15
0
10
50
15
0
10
0
35
5
20
40
10
0
10
0
30
15
10
5
0
0
10
0
0
40
0
15
10
50
0
10
0
10
0
15
5
10
0
0
10
40
P-PO4 (µg L-1)
30
20
25
5
10
40
15
5
15
30
20
5
10
5
5
10
55
30
10
5
50
5
10
15
20
15
0
0
5
5
0
10
0
5
20
30
0
40
0
5
0
10
5
10
0
0
50
40
N-NO3 (µg L-1)
20
35
20
35
30
0
30
10
45
0
45
10
40
10
40
20
5
0
50
25
10
35
10
20
40
30
70
20
30
60
20
0
30
20
5
0
80
10
45
30
20
60
45
20
30
0
25
0
SO42--(mg L-1)
% stones
20
15
25
30
15
30
10
5
15
10
20
30
25
5
0
20
20
30
5
5
30
35
20
30
15
20
20
20
15
20
45
50
5
25
20
20
0
40
0
5
55
10
10
55
40
0
15
20
Cond. (µS cm-1)
% silt
1
1
1
1
1
1
0
0
1
1
1
1
1
1
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
1
1
1
pH
% sand
1
1
0
1
0
2
2
0
2
0
0
0
1
0
0
0
0
4
0
0
0
0
0
0
3
0
0
0
1
0
0
0
0
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
% O2 saturation
% cobbles
3
6
5
7
6
6
7
0
3
9
4
5
0
7
3
0
9
5
9
8
4
8
9
9
6
4
9
6
5
8
5
9
7
7
9
7
1
3
9
3
7
0
3
6
6
9
8
7
Water Temp. (°C)
% gravel
3
3
4
4
1
2
2
0
4
5
3
5
4
2
4
2
3
1
2
4
4
2
4
5
3
3
1
3
2
3
2
1
1
4
4
4
1
4
4
5
4
5
3
5
4
1
3
2
Turbidity (NTU)
Regime
Discharge (L s-1)
Organic debris
Velocity (cm s-1)
Bryophytes
1
1
0
0
0
0
0
0
1
1
1
1
1
1
0
1
1
0
0
1
1
1
1
1
1
1
1
1
1
1
1
0
0
1
1
1
1
1
1
0
1
1
0
0
0
1
0
0
% rock
Canopy cover
AD0905 905
AD1077 1077
AD1235 1235
AD1300 1300
AD1665 1665
AD1790 1790
AD2314 2314
AD2739 2739
LD0584 586
LD0720 720
LD0928 928
LD0930 930
LD1400 1400
LD1502 1502
AN0430 430
AN1000 1000
AN1474 1474
AN1578 1578
AN1950 1950
BR0470 470
BR0658 658
BR0679 679
BR0790 790
BR0950 950
BR1315 1315
BR1358 1358
BR1379 1379
BR1436 1436
BR1605 1605
BR1765 1765
CS1350 1350
CA1642 1642
CA2153 2153
VZ1178 1178
MC1115 1115
PS1255 1255
PS1880 1880
CV0250 250
CV0854 854
CV0962 962
CV0992 992
CV1084 1084
CV1200 1200
CV1280 1280
CV1421 1421
CV1433 1433
CV1435 1435
CV1575 1575
Lithology
Altitude (m a.s.l.)
Spring code
Appendix 1. Environmental variables included in the data analyses. The first five are dummy variables: Lithology=
siliceous (0), limestone (1); Canopy cover= 0% (0), 0-25% (1), 25-50% (2), 50-75% (3), 75-100% (4); Bryophytes= 0, 1,
2….10 (quantitative); Organic debris= 0, 1, 2, 3, 4 (quantitative); Regime= permanent (1), intermittent (0). dl= detection
level.
16
V. Lencioni et al.
Bryophytes
Organic debris
Regime
%gravel
%cobbles
%sand
%silt
%stones
%crock
Velocity (m s-1)
Discharge (L s-1)
Turbidity (NTU)
Water Temp. (°C)
% O2 saturation
pH
Cond. (µS cm-1)
SO42--(mg L-1)
N-NO3 (µg L-1)
P-PO4 (µg L-1)
SiO2 (mg L-1)
0
0
0
0
0
1
1
1
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
4
2
4
1
1
4
4
2
4
1
5
4
5
5
0
2
4
2
5
2
3
4
2
3
3
2
5
2
2
3
1
4
4
3
8
9
0
6
3
6
7
7
3
0
9
3
9
8
4
7
4
7
7
3
0
5
8
5
4
3
8
7
7
3
3
5
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
2
0
0
0
0
0
0
1
3
3
0
1
4
2
1
0
0
1
1
1
1
1
1
1
1
1
0
1
1
1
1
1
1
1
1
1
1
0
1
1
1
0
0
1
1
1
1
1
1
1
50
40
35
50
25
65
40
10
40
0
35
5
35
0
0
30
10
40
0
25
5
15
35
25
5
0
35
50
45
10
15
35
10
20
15
45
20
10
10
35
10
40
10
30
65
25
50
5
50
20
20
45
25
10
45
25
50
10
35
45
0
20
55
0
10
20
20
0
0
20
10
15
5
0
0
10
5
5
10
0
0
0
10
10
30
10
25
15
15
0
0
0
0
30
20
5
5
40
0
10
25
5
10
10
0
10
0
10
5
5
10
15
0
0
0
10
0
5
0
10
25
10
0
10
5
0
20
10
0
5
10
0
0
0
0
0
5
10
10
10
10
70
5
15
15
0
5
20
30
30
0
40
50
0
15
25
50
25
20
0
5
30
0
5
30
0
0
15
0
40
0
0
70
0
5
20
0
0
50
90
0
20
0
10
0
0
0
0
0
25
35
0
0
0
0
70
0
40
10
10
10
15
25
10
15
5
30
15
20
8
3
30
21
15
40
7
10
10
15
1
15
5
4
5
50
40
40
16
15
50
25
1.0
0.1
1.5
0.2
3.0
1.0
0.5
3.0
2.0
6.0
2.0
3.0
0.2
4.0
6.5
0.5
0.6
0.2
0.3
0.5
1.0
0.5
0.8
0.2
0.1
0.1
2.3
1.0
1.0
0.7
0.2
10.0
0.3
0.05
0.09
0.15
0.70
0.23
2.84
0.13
0.54
0.04
0.55
0.19
0.34
0.28
0.07
0.48
0.48
0.48
0.88
0.28
0.15
0.17
0.14
1.66
0.50
0.50
0.50
0.61
0.69
0.69
0.69
0.76
0.24
0.01
6.3
4.7
4.9
6.6
1.0
8.0
4.4
4.0
4.5
2.1
9.3
4.3
9.5
9.8
11.8
11.9
8.4
6.6
8.6
8.3
12.4
9.0
7.1
10.1
3.1
8.9
7.7
8.0
8.9
6.8
5.5
7.8
11.0
79
89
84
65
79
80
95
83
81
93
83
80
80
95
80
83
90
87
67
77
78
80
83
80
90
83
77
80
77
75
77
88
87
7
7
7
7
7
8
8
8
7
7
8
8
8
8
8
8
8
8
8
7
8
8
8
8
8
8
8
8
8
8
8
8
8
62
46
43
30
37
568
223
144
60
136
240
207
413
341
266
485
360
261
393
354
234
241
204
580
320
590
297
300
310
480
202
261
340
2
6
3
2
1
154
7
1
11
54
2
7
8
6
5
5
4
4
7
2
7
10
5
4
4
4
35
25
13
86
13
3
4
231
772
165
298
347
254
605
287
108
163
654
543
1230
1271
2257
2257
1129
1823
304
265
2094
333
803
1257
1257
1257
659
677
677
903
916
703
915
7
1
3
1
4
4
1
1
4
1
1
3
4
14
11
12
12
8
1
4
15
2
7
7
7
7
3
3
3
3
1
4
1
9.9 12
4.7 <dl
7.9 <dl
7.5 <dl
4.6 <dl
4.7 <dl
5.2 <dl
0.6 <dl
9.8 <dl
3.6 <dl
2.0 <dl
1.6 54
4.7 <dl
4.0 <dl
4 100
3.7 30
3.7 <dl
3.2 <dl
5.2 <dl
4.6 <dl
3.6 <dl
5.6 <dl
3.7 <dl
2.8 <dl
2.9 <dl
2.9 <dl
2.1 <dl
2.1 <dl
2.1 <dl
2.1 <dl
1.7 <dl
2.9 <dl
1.9 <dl
Fe (µg L-1)
Canopy cover
CV1623 1623
CV1655 1655
CV1685 1685
CV1855 1855
CV2182 2182
LT1240 1240
MD16701670
MD18711871
OC2056 2056
OC2792 2792
PG0453 453
SL1724 1724
AT0972 972
MB0335 335
MB0385 385
MB0445 445
MB0517 517
MB1440 1440
BS0705 705
BS1527 1527
BC0170 170
BC0503 503
BC0565 565
ML0533 533
ML0580 580
ML0950 950
MP0656 656
MP0676 676
MP0690 690
MP0924 924
MP1566 1566
SC0250 250
VF0745 745
Lithology
Altitude (m a.s.l.)
Spring code
Appendix 1. Continuation.